Python/Python For Analytics
[ Python ] pandas plot 을 이용한 다양한 graph 그리기
Pydole
2023. 5. 24. 00:01
Pandas의 plot 을 이용하여 그래프 그리기
import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.rand(20,6),
columns=['a','b','c','d','e','f'])
line graph
df.plot.line(figsize = (15,5))
bar graph
df.plot.bar(figsize = (15,5), grid=True)
area graph
df.plot.area(figsize = (15,5), xticks = (1,5,10,15,20), yticks = (1,2,3,4,5))
area graph ( Time index )
import numpy as np
import pandas as pd
from datetime import datetime
from random import randint
data = [[ randint(50,1000) for x in range(4) ] for x in range(4) ]
ix = [ datetime(2023,5,randint(1,10)) for x in range(4) ]
df = pd.DataFrame(data,
columns=['a','b','c', 'd'],
index=ix)
df.plot.area(figsize=(10,5))
sctter graph
import numpy as np
import pandas as pd
x = [ x for x in range(100) ]
y = [ randint(50,100) for x in range(100) ]
df = pd.DataFrame(zip(x, y), columns=['x','y'])
df.plot.scatter(x='x',y='y',
s = 100,
c = 'red',
alpha=0.3)
파일저장은 matplotlib savefig를 이용
import matplotlib.pyplot as plt
plt.savefig('scatter.png') # png
plt.savefig('scatter.pdf') # pdf
그래프에 대한 옵션은 Document 를 참고 하면 되겠다.
Document : https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.plot.html#
pandas.DataFrame.plot — pandas 2.0.1 documentation
sequence of iterables of column labels: Create a subplot for each group of columns. For example [(‘a’, ‘c’), (‘b’, ‘d’)] will create 2 subplots: one with columns ‘a’ and ‘c’, and one with columns ‘b’ and ‘d’. Remaining colum
pandas.pydata.org